Fuzzy PID Controller Research Articles

Design and Force Control Analysis of a Novel Waist Massage Instrument

Background: There is a shortage of rehabilitation doctors and treatment equipment for patients with lumbar spondylosis. Therefore, a waist massage instrument (WMI) is designed to help patients alleviate lumbar pain. Objective: The objective of this study is to design a new WMI with the advantages of simple structure, lightweight, and function of effective force control, and to verify its function of palmar push, palmar press, and palmar vibration based on the on-off control, PID control, and fuzzy-PID control. Methods: Firstly, the movement characteristics of the Chinese massage manipulation are analyzed to clarify the design principle of the massage instrument. Then, a new WMI composed of massage head, vibration exciter, and actuator is designed to simulate the three massage manipulations. Next, the electric control system and control methods of on-off, PID, and fuzzy-PID controllers are introduced to realize the force control of WMI. Finally, the force control experiments of WMI are carried out to verify the function of the palmar press, palmar push, and palmar vibration based on the on-off control, PID control, and fuzzy-PID control, respectively. Results: The experimental results indicate that the proposed WMI can implement the massage manipulations of palmar push, palmar press, and palmar vibration well, and has good force control ability after using fuzzy-PID control. Conclusion: The newly designed WMI is effective in providing palmar push, palmar press, and palmar vibration massage manipulations for patients with lumbar spondylosis, and the fuzzy-PID controller improves the force control ability of the instrument. The WMI has the potential to be used as an effective treatment for lumbar pain.

Fuzzy neural network PID control design of camellia fruit vibration picking manipulator

Due to the growth characteristics of the flowers and fruits of camellia in the same period, the vibrating camellia fruit picking machine needs to ensure the constant rotational speed of the vibrating hydraulic motor when the picking mechanism is operating, to achieve a constant vibration frequency, to ensure that the camellia fruit can smoothly fall off the branches through vibration. In contrast, the camellia fruit does not fall off. In this regard, this paper deduced the state space equation of the camellia fruit picking machine’s valve-controlled vibrating hydraulic motor system and designed a fuzzy wavelet neural network PID controller (FWNN PID controller) based on the traditional incremental PID control principle. Then the designed vibration picking manipulator control system was simulated under no-load, 5 s load conditions, and load start conditions with MATLAB/Simulink, a general PID controller and a fuzzy RBF neural network PID controller (FRBFNN PID controller) were used to contrast with it. The results show that the general PID controller has a slow response speed and poor robustness, while fuzzy neural network PID controllers (including FWNN PID controller and FRBFNN PID controller) have a fast response speed and strong robustness, which can well meet the requirements of a specific vibration frequency. Finally, a field test was carried out. The results show that the FWNN PID control is better than the FRBFNN PID control. Furthermore, the FWNN PID controller obviously reduced the drop rate of camellia flowers within 6% while ensuring the picking efficiency above 90%, which can well meet the needs of the camellia fruit picking operation.

An Energy Consumption Optimization Method for Intelligent Transfer Robots in a Low-temperature Environment

The functional design and performance parameters of existing intelligent transfer robots (ITRs) have met the operational requirements for most scenarios at present. However, under the operation condition of low temperatures, the battery discharge capacity of ITRs will significantly reduce, resulting in a decrease in the efficiency of ITRs. Aiming at this problem, this paper proposes an energy consumption optimization method for intelligent transfer robots in a low-temperature environment, which can make the battery discharge capacity meet the best performance by adjusting the motion parameters of ITRs. Firstly, the optimal output current is obtained by analyzing the output characteristics of the battery in a low-temperature environment, and it is measured that the energy consumption of ITRs mainly depends on the energy used in the moving process. Then, it is proved that the moving speed of the ITR has the greatest influence on the output current of the battery based on comparative experiments. Next, the LSTM prediction model and fuzzy PID control are used to regulate the moving speed of the ITR, so that the output current of the robot battery can meet the optimal output performance in a low-temperature environment. Finally, extensive comparative experiments show that the energy consumption optimization method proposed in this paper can effectively improve the discharge capacity of robot batteries in a low-temperature environment.

Research on the Control Method of Anti-vibration Hammer Fastening Robot Operation for High-voltage Transmission Lines

The problem of low efficiency and high danger is addressed by mainly relying on the manual tightening of the anti-vibration hammer. A transmission line anti-vibration hammer fastening robot is designed, and its operation control method is focused on the study. Firstly, we use the visual YOLOV-5 algorithm to detect the anti-vibration hammer in real time to achieve rough positioning and then cooperate with the depth camera to obtain the accurate 3D coordinates of the anti-vibration hammer bolts. After obtaining the position of the anti-vibration hammer bolt, a fuzzy PID controller is used to control the robot’s operation motion to ensure the stability and accuracy of the operation. Finally, the tightening experiment of the anti-vibration hammer under the transmission line verifies that the proposed operation control method can meet the requirements of efficiency and reliable tightening of the anti-vibration hammer.

Determination of control area and design of fuzzy rule-tuned PID controller for LFC of multimachine power system

Determination of control area and design of fuzzy rule-tuned PID controller for LFC of multimachine power system

Multi-objective optimal design of a fuzzy adaptive robust fractional-order PID controller for a nonlinear unmanned flying system

In this study, a fuzzy adaptive robust fractional-order proportional-integral-derivative (FARFOPID) controller is introduced for stabilization of a nonlinear unmanned flying system. At first, a proportional-integral-derivative scheme improved by the fractional-order technique is employed to control the complicated dynamics of the considered system. An adaptive mechanism based on sliding surfaces is proposed to update the effective gains of the fractional-order PID controller. To improve the performance of the controller in the presence of disturbances and uncertainties, fuzzy systems are used to adjust the parameters of the sliding surfaces. The fuzzy systems, considered in this article, employ the singleton fuzzifier, product inference engine and center average defuzzifier as well as triangular-trapezoidal membership functions. Then, the multi-objective thermal exchange optimization (MOTEO), which has presented a high convergence speed and good performance for global search problems, is utilized to determine the controller parameters in such a way that control efforts and system errors would be minimized, simultaneously. Finally, simulation results clearly depict the effectiveness and efficiency of the proposed approach to handle the regarded unmanned flying system in comparison with other controllers.

Short Distance Detection and Control System Based on Photoelectric Sensor and Its Application in Target Detection of Handling Robot

The photoelectric sensor is an electronic device that is widely used in industrial automation processes. The device uses light to detect whether an object exists. The photoelectric sensor detection control system is the core part of the photoelectric sensor. The system includes sensor processing chip, control circuit, detection optical structure and automatic teaching control algorithm. In this research, the core control chip of the automatic teaching system and the core part of the control circuit of the short-distance photoelectric sensor are set up. The modular circuit around the above chip is designed. The optical structure of the sensor is designed by Position sensitive sensor (PSD) photoelectric accessories and triangulation method. Meanwhile, the core circuit control chip (CSP) is applied to complete the basic functions of the short-distance photoelectric sensor. Among them, the optical structure is designed to collect and process the optical signal of the detected object. Based on this, the I/V conversion is needed after collecting the optical signal by PSD, and then the signal processing is carried out. The fuzzy PID control model is used to solve the problem that the control object cannot accurately establish the mathematical model. The designed photoelectric sensor is used for the handling robot, and the D-H mathematical model of the handling robot is established. The Robotics toolbox provided by MatLab is used to simulate the movement of the robot, and the sensor is used to detect the target of the robot grabbing. The experimental results show that the sensor uploads the coordinate information of the object to be grabbed to the software interface, and the handling robot can accurately grab the object with the help of the photoelectric sensor, and place it in the corresponding position according to the appearance color of different objects to be grabbed.

Joint Simulation Study of Glass Greenhouse Roof Cleaning Machine Based on Adams and Matlab

The glass greenhouse roof cleaning machine is driven by dual motors, and there are problems with machine deflection and inconsistent speed of the two wheels during operation, to solve these problems, a joint simulation method based on Adams and Matlab is used in this project. Firstly, build detailed 3D models using SolidWorks software and Adams software, and set the necessary constraints and material properties for the models; then, the control system is modeled with Fuzzy-Proportion Integration Differentiation (PID) control algorithm in Matlab/Simulink module; finally, a joint simulation was performed using Adams software and Matlab/Simulink software. Through the analysis of the results of the joint simulation, the problem of inconsistent deflection and the two-wheel speed of the machine is optimized after the introduction of the Fuzzy-PID controller.

Control of Linear Electric Actuator with Hybrid Fuzzy PID Controller

In this study, the actuator, which converts circular motion to linear motion, is controlled with a smart hybrid controller. The model includes the analysis of electrical and mechanical parts. The controller, on the other hand, has a design methodology that cleverly blends classical PID (Proportional Integral Derivative) and fuzzy controllers. In this design methodology, classical PID and fuzzy controller have an error parameter dependent blending mechanism. In order to compare the performance of the hybrid controller, the coefficients of the classical PI and PID controllers were obtained by tuning and the coefficients with the best response were used. For performance comparison of conventional controllers and hybrid controllers; rise time, settling time, maximum overshoot and common performance indices values are used. The hybrid controller showed higher performance in terms of maximum overshoot, settling time, rising time and performance indices. The potential benefits of using a hybrid controller for the control of linear electric actuators were demonstrated by the fact that it performed better than conventional PID controllers on the majority of evaluation criteria.

Prediction for Hydrolysis of Ethylene Oxide via Fuzzy Logic and PID Control

Monoethylene glycol (MEG) or Ethylene Oxide is an important chemical in plastic and automotive industry as mixed ingredients or cooling liquid. It is produced from ethylene oxide via hydrolysis at 200ºC and 22 atm. The ratio of the ethylene oxide with water should be maintain at 1:20 to reduce the formation of diethylene glycol and higher homologs. Objective of this study is to predict a production of MEG using fuzzy logic. Others parameters such as level, temperature, composition and pressure are consider constant in this research as this study focusing on single input, single (SISO) output strategy. For fuzzy logic prediction, the type of model chosen is Mamdani with triangular membership function, input 1, input 2, and output which refer to error, feedback, and production of ethylene glycol respectively. 11 rules has been construct in this research. The rules may contain “AND” or “OR” conjunctions. The “error” represents the difference between the value feedback and the output. The results for fuzzy rules give highest product of MEG (6.91) at error of 0.102 and 0.8 of feedback. The gain of proportional, integral, and derivative are 0.2, 0.2, and 0.1 respectively.

Design of a Closed Piggery Environmental Monitoring and Control System Based on a Track Inspection Robot

To improve environmental quality in enclosed piggeries, a monitoring and control system was designed based on a track inspection robot. The system includes a track mobile monitoring platform, an environmental control system, and a monitor terminal. The track mobile monitoring platform consists of three main components: a single-track motion device, a main box containing electronic components, and an environmental sampling device. It is capable of detecting various environmental parameters such as temperature, humidity, NH3 concentration, CO2 concentration, light intensity, H2S concentration, dust concentration, and wind speed at different heights below the track. Additionally, it can control on-site environmental control equipment such as lighting systems, ventilation systems, temperature control systems, and manure cleaning systems. The networked terminal devices enable real-time monitoring of field equipment operating status. An adaptive fuzzy PID control algorithm is embedded in the system to regulate the temperature of the piggery. Field tests conducted on a closed nursery piggery revealed that the system effectively controlled the maximum temperature range within 2 °C. The concentrations of CO2, NH3, and PM2.5 were maintained at a maximum of 1092 mg∙m−3, 16.8 mg∙m−3, and 35 μg∙m−3, respectively. The light intensity ranged from 51 to 57 Lux, while the wind speed remained stable at approximately 0.35 m∙s−1. The H2S concentration was significantly lower than the standard value, and the lowest relative humidity recorded was 18% RH at high temperatures. Regular humidification is required in closed piggeries and other breeding places when the system does not trigger the wet curtain humidification and cooling function, as the relative humidity is lower than the standard value. By controlling the temperature, the system combined with a humidification device can meet environmental requirements. The control method is simple and effective, with a wide range of applications, and holds great potential in the field of agricultural environmental control.

Large Telescope Wind Load Estimation with Gradient Segments Superposition and its Servo Control

Obtaining the wind load distribution on the telescope aperture is very important to estimate its influence and reduce the wind disturbance on the telescope system. The aperture of the radio telescope structure can be as large as 100 m and therefore, the uniform wind load on the aperture assumption is not suitable for the radio telescope with large aperture. In this paper, a gradient segments superposition method for calculating the wind load has been proposed. The proposed method has been constructed by combining two regional divisions. First, reflecting surface has been evenly divided in the altitudinal direction. Second, the reflecting surface has been divided into several uniform rings assuming that the wind load coefficient on different rings are different. For the 110 m aperture radio telescope, the wind load estimation results differ by 28%. After that, a structural dynamics model of telescope has been established and a fuzzy PID controller has been designed to reduce wind disturbance. The Root Mean Square Error of telescope pointing under wind disturbance has been reduced by 67.8%. It is suggested that the proposed wind load estimation method has lay a solid foundation for the design of the large telescope system under wind disturbance.

Mitigation of circulating current and common mode voltage in grid-connected induction motor drive using modified PID-fuzzy controller

Mitigation of circulating current and common mode voltage in grid-connected induction motor drive using modified PID-fuzzy controller

Temperature monitoring system of beer fermentation and brewing based on immune fuzzy PID controller

AbstractBeer is one of the popular drinks, the temperature control in the process of beer fermentation plays a crucial role. The current temperature control method mainly uses the traditional PID control, but its control adjustment time is long, the overshoot is large, the control effect still needs to be improved. A beer fermentation and brewing temperature monitoring system based on immune fuzzy PID controller was designed in this experiment. Immune fuzzy PID controller is a nonlinear controller, which combines the advantages of traditional PID controller and fuzzy controller and refers to the regulatory mechanism of biological immune system, and obtains good suitable characteristics by controlling the parameter values of the system. PID converts the rule information into fuzzy information by fuzzy basic theory and stores it in computer database. By referring to the actual situation of PID, the computer uses fuzzy reasoning to adjust the PID parameters. The beer fermentation temperature monitoring system based on the traditional PID controller is compared with the proposed system. Under the control of the designed temperature monitoring system, the temperature has a certain effect on the fermentation speed of beer. The fermentation time of high temperature fermentation (16°C) is 3 days shorter than that of normal temperature fermentation (10°C). The robustness and applicability of the system are verified.

Efficient Power Management and Control Strategy of Hybrid Renewable Energy System in Microgrid

Currently, the use of renewable energy has gradually increased due to the environmental problems present nowadays. The intermittency of distributed renewable generation poses significant challenges for the operation and integration of microgrids. Unlike the main power grid, where load balancing resources, in general, are abundant, the balancing of generation and load in a microgrid must be done by small gas turbines, diesel generators, or energy storage devices with very limited capacity and at much higher costs. Consequently, the proposed methodology seeks a model for minimizing the Energy Cost (EC) and enhancing the power supply for rural areas by designing and analyzing four different hybrid system configurations based on integrating a biomass system with a photovoltaic (PV), wind turbine (WT) and battery system. To ensure the desired power demand with minimum production cost, the research proposed an energy-efficient Hybrid DC/AC microgrid using four renewable energy sources. Lithium-ion batteries were chosen for this study due to their high energy density, long life cycle, and high efficiency. The existence of both AC and DC microgrids has led to a new concept of hybrid AC/DC microgrids which consists of both AC and DC grids tied by an Interlinking Converter (ILC). It comprises a DC grid and AC grid interlinked by a bidirectional DC/AC converter. Such a hybrid AC/DC microgrid has the advantages of both AC and DC with increased efficiency and less cost. To provide higher voltages, the Multi-Input Booster (MIB) DC-DC converters are used as a power converter in between load and source to enforce and increase the PV depending on the voltage output signal. Further extract maximum power from the solar PV system, perturb and observe algorithm-based power point tracking control mechanism is proposed DC link voltage of ILC is regulated usually by DC side control in load sharing among sources in the DC microgrid. In addition, to overcome the load fluctuation problem in a microgrid, the research introduced a Mamdani type 2 PID-fuzzy controller. Performance index parameters of the transient response characteristics are also improved by using the proposed control approach. The time-domain dynamic responses reveal that the proposed type-II fuzzy PID controller can balance the power generation and demand properly and control both system frequency and tie-line power effectively.

Metaheuristic-Based Algorithms for Optimizing Fractional-Order Controllers—A Recent, Systematic, and Comprehensive Review

Metaheuristic optimization algorithms (MHA) play a significant role in obtaining the best (optimal) values of the system’s parameters to improve its performance. This role is significantly apparent when dealing with systems where the classical analytical methods fail. Fractional-order (FO) systems have not yet shown an easy procedure to deal with the determination of their optimal parameters through traditional methods. In this paper, a recent, systematic. And comprehensive review is presented to highlight the role of MHA in obtaining the best set of gains and orders for FO controllers. The systematic review starts by exploring the most relevant publications related to the MHA and the FO controllers. The study is focused on the most popular controllers such as the FO-PI, FO-PID, FO Type-1 fuzzy-PID, and FO Type-2 fuzzy-PID. The time domain is restricted in the articles published through the last decade (2014:2023) in the most reputed databases such as Scopus, Web of Science, Science Direct, and Google Scholar. The identified number of papers, from the entire databases, has reached 850 articles. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was applied to the initial set of articles to be screened and filtered to end up with a final list that contains 82 articles. Then, a thorough and comprehensive study was applied to the final list. The results showed that Particle Swarm Optimization (PSO) is the most attractive optimizer to the researchers to be used in the optimal parameters identification of the FO controllers as it attains about 25% of the published papers. In addition, the papers that used PSO as an optimizer have gained a high citation number despite the fact that the Chaotic Atom Search Optimization (ChASO) is the highest one, but it is used only once. Furthermore, the Integral of the Time-Weighted Absolute Error (ITAE) is the best nominated cost function. Based on our comprehensive literature review, this appears to be the first review paper that systematically and comprehensively addresses the optimization of the parameters of the fractional-order PI, PID, Type-1, and Type-2 fuzzy controllers with the use of MHAs. Therefore, the work in this paper can be used as a guide for researchers who are interested in working in this field.

Fuzzy Neural Network PID Control Used in Individual Blade Control

In order to further reduce the vibration level of helicopters, the active vibration control technology of helicopters has been extensively studied. Among them, individual blade control (IBC) independently applies high-order harmonics to each blade with an actuator, which can improve the aerodynamic environment of the blade and effectively reduce the vibration load of the hub. The rotor structural dynamics model based on the Hamilton energy variation principle and the medium deformation beam theory were established firstly, and the aerodynamic model based on the dynamic inflow model and the Leishman–Beddoes unsteady aerodynamic model were also established. The structural finite element method and the direct numerical integration method were used to calculate the vibration response of the rotor to determine the vibration load of the hub. After these, the steepest descent-golden section combinatorial optimization algorithm was used to find the optimization parameters of IBC. Based on this, the input parameters of fuzzy neural network PID control were determined, and the rotor hub vibration load control simulation was conducted. Under the effect of IBC, the vibration loads of the hub could be reduced by about 60%. The article gives the best control laws of individual harmonic pitch control and their combinations. These results can theoretically be applied to the design of control law to reduce helicopter vibration loads.

Clamping Force Control Strategy of Electro-Mechanical Brake System Using VUF-PID Controller

Clamping force control is one of the key technologies in the algorithm design and implementation of electro-mechanical braking system, whose control effects directly affect the vehicle braking performance and safety performance. In order to improve the clamping force control performance of electro-mechanical braking (EMB) system, an EMB clamping force control method based on Variable universe adaptive fuzzy PID (VUF-PID) controller is proposed, and stretching factors are added to the fuzzy PID control. According to the operation of the controlled object, the fuzzy theory domain can be adjusted in real time to keep the system in the proper parameter value and improve the adaptive ability of the system. The response characteristics and effectiveness of clamping force under step braking condition, gear switching braking condition and sine braking condition are verified by simulation experiments using MATLAB/Simulink. The results show that the proposed VUF-PID control method has strong tracking characteristics and stability characteristics, and meet the braking requirements under different braking conditions.

Fuzzy PID control system optimization and verification for oxygen-supplying management in live fish waterless transportation

Live fish waterless transportation could be recognized as an essential supplement for water-based transportation due to its low oxygen consumption and less waste water pollution. The critical problem to maintaining the fish survival quality under such a unique transport strategy is accurately controlling the oxygen concentration in the container to be constantly at stable and high levels. This paper aims to propose an improved fuzzy PID control system based on the grey model with residual rectification by improved particle swarm optimized Gated Recurrent Unit (GM-IPSO-GRU) to realize advanced oxygen level control. In addition, it is also reinforced by adopting the improved grey wolf optimization (IGWO) for the majorization of control parameters (quantization factors, scale factors) with full consideration of fish size features. In this study, Turbot (Scophthalmus maximus) is taken as the test subject to verify the integrated control performance of the optimized fuzzy PID controller through simulated waterless live transportation under low-temperature conditions. The proposed control system is validated as more efficient than the traditional proportional integral derivative (PID) and fuzzy PID algorithms for handling its nonlinear, time-varying, and time lag problems well. In summary, the control group experiment shows that the newly-designed control system has the advantages of shorter stabilization time, minor overshoot, and strong anti-interference ability for oxygen level adjustment. Finally, applying this novel control technology can effectively improve oxygen adjustment efficiency and provide feasible quality control support for the deep optimization of the live fish circulation industry.

Simulation Study on Digital Control Model of Fiber Optic Gyro SLD Light Source

Fiber Optic Gyroscope is an angular velocity sensitive device based on Sagnac effect. Super Luminescent Diode (SLD) is a widely used light source in fiber optic gyroscope, and its characteristics will directly affect the overall performance of gyroscope. In this paper, the working mechanism of SLD light source is studied, and the photoelectric characteristics of SLD light source and the influence of light source temperature and driving current on center wavelength are analyzed. According to the relationship between the central wavelength of the light source and the driving current and die temperature, a three-dimensional model of the central wavelength of the light source is obtained. In order to control the driving current and die temperature quickly and stably, the fuzzy PID control scheme of die temperature and incremental PID control scheme of driving current are studied and designed. Based on the three-dimensional model of the center wavelength of light source, the center wavelength of SLD light source is controlled stably and quickly.